LIDARs have been used in various applications for detecting stationary and moving objects. For example, LIDARs are increasingly being implemented in vehicle collision avoidance systems to detect stationary and moving vehicles to avoid traffic collisions. In a conventional LIDAR system, detection of objects is achieved by scanning a laser beam in a predetermined scan pattern. For example, a laser beam in a conventional LIDAR system may be redirected by reflecting the laser beam from a moving or rotating mirror. The moving or rotating mirror may be mechanically controlled, for example, by a micro-electro-mechanical system (MEMS). Such mechanical or MEMS controlled mirrors are capable of scanning the laser beam in predetermined patterns but are typically not capable of foveation, that is, pointing the beam in random directions, or pointing the beam to different spots at different times not based on a predetermined scan pattern. Diffraction-based liquid-crystal-on-silicon (LCOS) beam steering may be capable of foveation, but the switching rates of typical LCOS systems are relatively low.
In typical highway traffic, two vehicles traveling in opposite directions may approach each other at a high relative velocity. If one of the vehicles is equipped with a conventional LIDAR system with a relatively low rate of scan, the two vehicles may have traveled a significant distance toward each other between two consecutive scans. On the other hand, if laser beam scanning is limited to a narrow sector in an attempt to improve the rate of scan, then vehicles outside that sector may not be detected. In order to provide effective vehicle detection and collision avoidance, it is desirable that vehicles be equipped with LIDAR systems that are capable of both scanning wide areas in which objects of interest may be found and providing fast updates on objects of interest within those areas, for example, fast-approaching vehicles.